[mlir] Use RankedTensorType when rank is required

[mlir] Use RankedTensorType when rank is required

`RankedTensorOf` and `TensorRankOf` (in Tablegen files) now generate code that uses `RankedTensorType` instead of `TensorType`. This gives us more accurate type information (e.g., when calling `op.getType()`).

Also use restrict tensor.expand_shape/tensor.collapse_shape/tensor.pad to ranked tensors. Only cast ops should deal with unranked tensors.

Also improves a few places in the code base (e.g., Toy tutorial) where a ranked tensor is assumed (e.g., because `getRank` is called) but a `TensorType` is currently used: cast to `RankedTensorType` directly, so that the assertion is triggered directly at the cast.

Differential Revision: https://reviews.llvm.org/D147149